
#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#include "helper_cuda.h"
#include "helper_functions.h"

#include "helper_string.h"

#include <stdio.h>

using namespace std;

cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size);

__global__ void addKernel(int *c, const int *a, const int *b)
{
    int i = threadIdx.x;
    c[i] = a[i] + b[i];
}



bool InitCUDA() {
	int count, dev;
	checkCudaErrors(cudaGetDeviceCount(&count));
	if (count == 0) {
		fprintf(stderr, "There is no device.\n");

	}
	else {
		printf("\n%d Device(s) Found\n", count);
		checkCudaErrors(cudaGetDevice(&dev));
		printf("The current Device ID is %d\n", dev);

	}

	int i = 0;
	bool bValid = false;
	cout << endl << "The following GPU(s) are detected:" << endl;
	for (i = 0; i < count; i++) {
		cudaDeviceProp prop;
		if (cudaGetDeviceProperties(&prop, i) == cudaSuccess) {
			cout << "------------Device" << i << "------------------" << endl;
			cout << prop.name << endl;
			cout << "Total global memory:" << prop.totalGlobalMem << " Byte" << endl;
			cout << "Maximum share memory per block: " << prop.sharedMemPerBlock << " Byte" << endl;
			cout << "Maximum registers per block:" << prop.regsPerBlock << endl;
			cout << "Wrap size:" << prop.warpSize << endl;
			cout << "Maximum threads per block:" << prop.maxThreadsPerBlock << endl;
			cout << "Maximum block dimensions:[" << prop.maxThreadsDim[0] << ", " << prop.maxThreadsDim[1] << ","
				<< prop.maxThreadsDim[2] << "]" << endl;
			cout << "Maximum grid dimensions:[" << prop.maxGridSize[0] << ","
				<< prop.maxGridSize[1] << ","
				<< prop.maxGridSize[2] << "," << "]" << endl;
			cout << "Total constant memory :" << prop.totalConstMem << endl;
			cout << "Supports compute Capability:" << prop.major << "."
				<< prop.minor << endl;
			cout << "Kernel frequency: " << prop.clockRate << "kHz" << endl;
			if (prop.deviceOverlap)
				cout << "Concurrent memory copy is supported." << endl;
			cout << "Number of multi-processors: "
				<< prop.multiProcessorCount << endl;
			if (prop.major >= 1) {
				bValid = true;
			}
		}
	}

	cout << "-------------------------------" << endl;

	if (!bValid) {
		fprintf(stderr, "There is no device supporting CUDA 1.x.\n");
		return false;
	}

	checkCudaErrors(cudaSetDevice(0));

	return true;
}



int main()
{
    const int arraySize = 5;
    const int a[arraySize] = { 1, 2, 3, 4, 5 };
    const int b[arraySize] = { 10, 20, 30, 40, 50 };
    int c[arraySize] = { 0 };

	bool sanck = InitCUDA();


    // Add vectors in parallel.
    cudaError_t cudaStatus = addWithCuda(c, a, b, arraySize);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "addWithCuda failed!");
        return 1;
    }

    printf("{1,2,3,4,5} + {10,20,30,40,50} = {%d,%d,%d,%d,%d}\n",
        c[0], c[1], c[2], c[3], c[4]);

    // cudaDeviceReset must be called before exiting in order for profiling and
    // tracing tools such as Nsight and Visual Profiler to show complete traces.
    cudaStatus = cudaDeviceReset();
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaDeviceReset failed!");
        return 1;
    }

    return 0;
}

// Helper function for using CUDA to add vectors in parallel.
cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size)
{
    int *dev_a = 0;
    int *dev_b = 0;
    int *dev_c = 0;
    cudaError_t cudaStatus;

    // Choose which GPU to run on, change this on a multi-GPU system.
    cudaStatus = cudaSetDevice(0);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaSetDevice failed!  Do you have a CUDA-capable GPU installed?");
        goto Error;
    }

    // Allocate GPU buffers for three vectors (two input, one output)    .
    cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(int));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

    cudaStatus = cudaMalloc((void**)&dev_a, size * sizeof(int));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

    cudaStatus = cudaMalloc((void**)&dev_b, size * sizeof(int));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

    // Copy input vectors from host memory to GPU buffers.
    cudaStatus = cudaMemcpy(dev_a, a, size * sizeof(int), cudaMemcpyHostToDevice);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }

    cudaStatus = cudaMemcpy(dev_b, b, size * sizeof(int), cudaMemcpyHostToDevice);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }

    // Launch a kernel on the GPU with one thread for each element.
    addKernel<<<1, size>>>(dev_c, dev_a, dev_b);

    // Check for any errors launching the kernel
    cudaStatus = cudaGetLastError();
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
        goto Error;
    }
    
    // cudaDeviceSynchronize waits for the kernel to finish, and returns
    // any errors encountered during the launch.
    cudaStatus = cudaDeviceSynchronize();
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
        goto Error;
    }

    // Copy output vector from GPU buffer to host memory.
    cudaStatus = cudaMemcpy(c, dev_c, size * sizeof(int), cudaMemcpyDeviceToHost);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }

Error:
    cudaFree(dev_c);
    cudaFree(dev_a);
    cudaFree(dev_b);
    
    return cudaStatus;
}
